The present exemplary embodiment relates to the gaming arts. It finds particular application in conjunction with the creation of bingo faces, and will be described with particular reference thereto. However, it is to be appreciated that the present exemplary embodiment is also amenable to other like gaming applications where a plurality of numbers or other indicia need to be generated.
In the gaming industry, there are many games in which a player receives a set of random numbers and waits for winning numbers to be called, hoping that the winning numbers match their own numbers. Such games include Keno, lottery, Bingo, and others. In games such as these, non-repeating combinations of numbers, symbols, or other types of indicia have many practical applications. For example, it is often desirable to ensure that repeating number combinations do not occur, as it might lead to duplicate winners, decreasing the payout potential to any single individual. In these types of games, unique number sets or other gaming pieces can eliminate duplicate winners, minimize the occurrence of multiple winners, and add excitement to the game by eliminating players from seeing the same game pieces on different occasions.
Various methods exist to create and store unique combinations of numbers. For instance, some systems employ completely random number generation. In this type of system, the numbers are generated randomly, and the product is then compared to a host of already created similar combinations stored in a memory. If the randomly generated number combination already exists in the memory, then it is discarded as a duplicate, and the process is repeated.
Unfortunately, in this type of number generation scheme, development and storage of the non-repeating combinations can be a rather monumental task, given the vast quantity of combinations that are possible. Consider for instance, a Bingo face that consists of a 5×5 number array. The first column contains 5 numbers, selected from 1-15, in random order. The second, fourth, and fifth columns are similar, containing the numbers 16-30, 46-60, and 61-75, respectively. The third, or middle column contains four numbers selected from 31-45. The middle space in the third column contains a “free” space. Given this number arrangement scheme, there are over 111 quintillion (1.11×1017) unique combinations. Typically, storing a single bingo card face requires 12 bytes, requiring well over one-sextillion (1×1018) bytes to store all of the combinations. To put this in perspective, a typical computer hard drive holds about 100 gigabytes (100 billion bytes). Therefore, it would take over 13 million hard drives to hold the 1.11×1017 number combinations. Additionally, as more and more bingo faces are stored, it takes longer and longer to compare new ones against the stored ones in order to check for uniqueness.
It is apparent that the storage of such vast amounts of unique bingo faces is prohibitive. Therefore, it is desirable to find an alternate means of efficiently creating large quantities of non-repeating bingo faces. The present application provides a new and improved method and apparatus that overcomes the above-referenced problems as well as others.